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alphafold-database

Retrieve AlphaFold protein structures by UniProt ID and analyze pLDDT and PAE metrics.

557|98|Updated Nov 7, 2025
Search Tags:#bioinformatics#protein structure#drug discovery#alphafold#uniprot#structural biology
One-click install
npx skills add https://github.com/jimmc414/Kosmos --skill alphafold-database-jimmc414
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: alphafold-database
Source: https://github.com/jimmc414/Kosmos/tree/main/kosmos-claude-scientific-skills/scientific-skills/alphafold-database
Command: npx skills add https://github.com/jimmc414/Kosmos --skill alphafold-database-jimmc414

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill requires biopython, requests, numpy, matplotlib, pandas, scipy, google-cloud-bigquery, gsutil, and includes scripts (resource) and references (resource) components.

What problem does it solve?

This Skill provides access to over 200 million AI-predicted 3D protein structures, enabling researchers to analyze protein architecture and function even when experimental data is unavailable.

Core Features & Use Cases

  • Structure Retrieval: Fetch protein structures by UniProt ID.
  • Confidence Analysis: Evaluate prediction reliability using pLDDT and PAE metrics.
  • Bulk Data Access: Download entire proteomes via Google Cloud.
  • Use Case: A structural biologist needs to investigate the potential binding site of a newly identified protein. They use this Skill to download the AlphaFold prediction, analyze its confidence, and visualize the structure to identify potential drug targets.

Quick Start

Use the alphafold-database skill to download the structure for UniProt ID P00520.

Frequently Asked Questions about alphafold-database

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I download AlphaFold predicted protein structures using a UniProt ID?▼

You can download AlphaFold predicted protein structures by providing a UniProt ID to retrieve 3D protein structure files in PDB or mmCIF format programmatically.

What do pLDDT and PAE metrics tell me about AI-predicted protein structures?▼

pLDDT and PAE metrics evaluate the reliability of AI-predicted protein structures. Analyzing these confidence scores helps determine the accuracy of specific structural regions for drug discovery.

Can I download entire proteomes from the AlphaFold database via Google Cloud?▼

Yes, you can download entire proteomes from the AlphaFold database via Google Cloud, enabling bulk data access for large-scale structural biology research and protein engineering.

Does this AlphaFold database access method require Biopython and NumPy?▼

Yes, accessing the AlphaFold database and analyzing protein structures requires dependencies including Biopython, NumPy, pandas, and matplotlib to process structural data and confidence metrics.

What's the best way to analyze protein binding sites for drug discovery without experimental data?▼

Retrieving AI-predicted 3D protein structures via AlphaFold allows you to investigate potential binding sites and identify drug targets even when experimental structural data is unavailable.

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